An Improved Algorithm of the Maximum Entropy Image Segmentation

被引:6
|
作者
He, Yan [1 ]
Jie, Liu [1 ]
Yang Dehong [1 ]
Pu, Wang [1 ]
机构
[1] Chongqing Univ Technol, Coll Comp Sci, Chongqing 400054, Peoples R China
来源
2014 Fifth International Conference on Intelligent Systems Design and Engineering Applications (ISDEA) | 2014年
关键词
Image Segmentation; Maximum Entropy; Arithmetic Mean; Binarization;
D O I
10.1109/ISDEA.2014.255
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
For improving the accuracy of the traditional maximum entropy threshold segmentation algorithm, an improved maximum entropy segmentation algorithm is proposed. Firstly, it determines the possible range of an optimal segmentation threshold according to a simple statistical method, so as to reduce the interference of the background and magnify the proportion of the target region. Secondly, in a certain range of threshold, does image segmentation according to an optimal segmentation threshold, which is obtained by using maximum entropy principle. Simulation experiments show that the improved algorithm not only can improve accuracy and noise immunity effectively, but also can better keep the details of the target region in comparison with the traditional maximum entropy threshold segmentation algorithm.
引用
收藏
页码:157 / 160
页数:4
相关论文
共 50 条
  • [31] Image segmentation algorithm based on the improved watershed algorithm
    Sun, Huijie
    Deng, Tingquan
    Li, Yanchao
    Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University, 2014, 35 (07): : 857 - 864
  • [32] Research of segmentation method on color image of Lingwu long jujubes based on the maximum entropy
    Wang, Yutan
    Dai, Yingpeng
    Xue, Junrui
    Liu, Bohan
    Ma, Chenghao
    Gao, Yaoyao
    EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING, 2017, : 1 - 9
  • [33] 2-D Maximum Entropy Method of Image Segmentation Based on Differential Evolution
    Zhang Shaojuan
    Jia Cunliang
    Liu Jingzhi
    Dong Lifang
    PROCEEDINGS OF THE SECOND INTERNATIONAL SYMPOSIUM ON TEST AUTOMATION & INSTRUMENTATION, VOLS 1-2, 2008, : 792 - 795
  • [34] Marine Spill Oil SAR Image Segmentation Based on Maximum Entropy and CV Model
    Ji, Yang
    Wu, Yiquan
    Shen, Yi
    FOUNDATIONS OF INTELLIGENT SYSTEMS (ISKE 2011), 2011, 122 : 427 - 435
  • [35] Research of segmentation method on color image of Lingwu long jujubes based on the maximum entropy
    Yutan Wang
    Yingpeng Dai
    Junrui Xue
    Bohan Liu
    Chenghao Ma
    Yaoyao Gao
    EURASIP Journal on Image and Video Processing, 2017
  • [36] Improved Random Walker Interactive Image Segmentation Algorithm for Texture Image Segmentation
    Yi Yufeng
    Gao Yang
    Li Wenna
    Gao Liqun
    2011 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, 2011, : 4163 - 4166
  • [37] An Improved Suppressed FCM Algorithm for Image Segmentation
    Lan, Hong
    Jin, Shaobin
    ADVANCES IN MANUFACTURING SCIENCE AND ENGINEERING, PTS 1-4, 2013, 712-715 : 2349 - 2353
  • [38] An Image Segmentation Algorithm Based On Improved PCNN
    Song, Yin-mao
    Ren, Shu-bin
    Liu, Guole
    PROCEEDINGS OF 2010 INTERNATIONAL SYMPOSIUM ON IMAGE ANALYSIS AND SIGNAL PROCESSING, 2010, : 25 - 30
  • [39] Research on an improved watershed algorithm to image segmentation
    Chen, Jie
    Lei, Meng
    Fan, Yao
    Gao, Yi
    PROCEEDINGS OF 2012 7TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION, VOLS I-VI, 2012, : 1917 - 1919
  • [40] Image segmentation algorithm based on improved PCNN
    Chen Hong
    Wu Chengdong
    Yu Xiaosheng
    Wu Jiahui
    LIDAR IMAGING DETECTION AND TARGET RECOGNITION 2017, 2017, 10605